Pemodelan Regresi

Model Regresi

Model regresi

m <- lm(math~ 1, data = skor)
d <- coef(summary(m))
knitr::kable(d)

	Estimate	Std. Error	t value	Pr(>|t|)
(Intercept)	402.3658	2.963256	135.785	0

Garis regresi

p1 <- ggplot(data = skor, aes(x=growth, y = math, color = CNTSCHID))+ xlim(1,4)+
geom_point()+
geom_jitter() +  
geom_smooth(method="lm", se = FALSE)+
theme_bw()
print(p1)

`geom_smooth()` using formula = 'y ~ x'

Warning: The following aesthetics were dropped during statistical transformation: colour
i This can happen when ggplot fails to infer the correct grouping structure in
  the data.
i Did you forget to specify a `group` aesthetic or to convert a numerical
  variable into a factor?

Warning: Removed 101 rows containing missing values (`geom_point()`).

Sebaran Skor Matematika per sekolah

skor %>% 
  ggplot(aes(math)) + 
  geom_density() +
  facet_wrap(~CNTSCHID)

Distribusi Growth Mindset per sekolah

skor %>% 
  ggplot(aes(growth)) + 
  geom_bar() +
  facet_wrap(~CNTSCHID)